Platforms that provide GPU compute, model hosting, and inference APIs. These companies serve open-source and third-party models, offer optimized inference engines, and provide cloud GPU infrastructure for AI workloads.
28 tools compared · Layer 1 · Updated April 29, 2026
Ranked by community traction, recent activity, and breadth of capabilities. Tap any tool for full pros, cons, pricing, and alternatives.
NVIDIA is the dominant force in AI computing hardware, providing the GPU accelerators that power the vast majority of AI training and inference workloads worldwide. Founded in 1993 by Jensen Huang, Chris Malachowsky, and Curtis Priem, the company evolved from a graphics chip maker into the backbone of the AI revolution. Its H100 and Blackwell B200 GPUs are the industry standard for training large language models, and its CUDA software ecosystem has created a deep moat that makes switching to alternative hardware difficult for most AI teams.
+Unmatched GPU performance for AI training and inference
llama.cpp is the foundational C/C++ inference engine that redefined what's possible for running large language models outside of multi-billion-dollar data centers. With 107,000+ GitHub stars, it's the backbone of nearly every local-LLM tool — Ollama, LM Studio, GPT4All, Open WebUI, and countless others build on llama.cpp's runtime.
+The de-facto standard for local LLM inference
CoreWeave is a specialized cloud infrastructure provider founded in 2017 in New Jersey by Michael Intrator, Brian Venturo, Brannin McBee, and Peter Salanki. Originally started by three commodities traders, CoreWeave has grown into a leading GPU cloud platform built specifically for AI and machine learning workloads. Based in Livingston, New Jersey, with approximately 1,871 employees as of January 2026, CoreWeave offers on-demand access to NVIDIA H100 and A100 GPUs with significantly lower pricing than traditional hyperscalers. The platform provides Kubernetes-native orchestration, fast networking, and flexible scaling, making it popular with AI labs, research institutions, and startups that need large GPU clusters without long-term commitments. CoreWeave's infrastructure is designed from the ground up for GPU-accelerated workloads, offering up to 60% discounts over on-demand prices for committed usage, with transparent pricing that doesn't charge for data egress, IOPS, or core networking services.
+Significantly lower GPU pricing compared to AWS, Azure, and GCP hyperscalers
Groq is an AI infrastructure company founded in 2016 by former Google engineers, including Jonathan Ross (one of the designers of Google's Tensor Processing Unit) and Douglas Wightman. Headquartered in Mountain View, California, Groq provides specialized AI compute solutions focused on accelerating AI inference workloads using its custom-built Language Processing Unit (LPU) hardware. The company's platform offers some of the most competitive pricing in the AI inference market, with ultra-low latency and exceptional throughput. Groq provides access to models from multiple providers including OpenAI, Anthropic, Google, Cohere, and Mistral through a pay-as-you-go model charging per token consumed. The company offers three billing tiers—Free, Developer, and Enterprise—with additional cost-saving features like Batch API (50% discount) and Prompt Caching (50% discount on cache hits). With offices across North America and Europe, Groq has established itself as a leading alternative to traditional cloud GPU providers, particularly for teams optimizing for inference speed and cost efficiency.
+Exceptional inference speed with ultra-low latency using custom LPU hardware
Together AI is a cloud-based platform for building with open-source generative AI, founded on June 11, 2022 in San Francisco by Ce Zhang, Chris Re, Percy Liang, and Vipul Ved Prakash. The company raised USD 305 million in Series B funding in 2025 with participation from industry leaders including NVIDIA and Salesforce Ventures. Together AI provides serverless inference with pay-as-you-go pricing starting from USD 0.10 per million tokens for small models and USD 0.90 for Llama 3 70B, with a free USD 5 credit to start. The platform offers a 50 percent discount on batch inference and 50 percent savings on prompt caching for repetitive queries. For teams requiring dedicated resources, Together AI provides GPU endpoints billed per minute, with high-end H100 and H200 GPUs available. The platform specializes in open-source model deployment and provides instant GPU clusters for training and inference workloads. Together AI has become a leading platform for teams building with open-source AI models, offering both serverless convenience and dedicated infrastructure options.
+Competitive pricing starting at USD 0.10 per million tokens
Nebius (Nasdaq: NBIS) is a major GPU cloud provider spun off from Yandex, offering large-scale NVIDIA GPU clusters for AI training and inference. With data centers in Europe and expanding globally, Nebius provides enterprise-grade AI infrastructure with competitive pricing and dedicated support for large-scale AI workloads.
GPT4All is Nomic AI's open-source local LLM platform — runs LLMs on Windows, macOS, and Linux with full customization, GPU acceleration via Vulkan/Metal/CUDA, and a killer LocalDocs feature for document RAG against your local files. 77K+ GitHub stars, designed for enterprise use with usage analytics and centralized model distribution.
Lambda provides GPU cloud infrastructure and workstations purpose-built for deep learning. Their cloud platform offers on-demand access to NVIDIA H100 and A100 GPUs with pre-installed ML frameworks. Lambda also sells GPU workstations and servers for on-premises AI development. Known for competitive pricing and developer-friendly tooling, Lambda serves AI researchers and companies needing dedicated GPU compute.
Anyscale is the company behind Ray, the open-source distributed computing framework used by OpenAI, Uber, and Spotify for scaling AI workloads. Anyscale's platform provides managed Ray clusters for distributed training, batch inference, and model serving, making it easy to scale AI applications across hundreds of GPUs.
Cerebras builds the world's largest AI chips—wafer-scale processors that contain millions of cores on a single silicon wafer. The Cerebras CS-2 system delivers massive parallelism for AI training and ultra-fast inference for open-source models. Through Cerebras Inference, developers can access some of the fastest LLM inference speeds available, particularly for Llama models.
Fireworks AI is a generative AI inference platform that offers fast, cost-efficient model serving. The platform hosts popular open-source models and supports custom model deployments with optimized inference using proprietary serving technology. Fireworks specializes in compound AI systems with features like function calling, JSON mode, and grammar-guided generation that make it easy to build structured AI applications.
Modal is a serverless cloud platform for running AI workloads with zero infrastructure management. Developers write Python code and Modal handles containerization, GPU provisioning, scaling, and scheduling automatically. The platform supports GPU-accelerated functions, scheduled jobs, web endpoints, and batch processing, making it particularly popular for ML pipelines, model serving, and data processing tasks.
Prime Intellect is a decentralized AI compute platform that enables distributed training and inference across globally distributed GPU clusters. It focuses on making large-scale AI training accessible by aggregating compute resources from multiple providers, enabling researchers to train frontier-scale models without relying on centralized cloud providers.
Replicate is a platform for running AI models in the cloud with a simple API. It hosts thousands of open-source models including Llama, Stable Diffusion, and Whisper, letting developers run them with a single API call. Replicate handles GPU provisioning, scaling, and model optimization automatically.
RunPod is a cloud GPU platform offering on-demand and spot GPU instances for AI training, inference, and development. Known for competitive pricing and a simple developer experience, RunPod provides NVIDIA A100, H100, and consumer-grade GPUs with serverless endpoints, persistent storage, and Docker-based environments. Popular with indie developers, researchers, and startups for running Stable Diffusion, LLM fine-tuning, and custom AI workloads.
SambaNova builds custom AI chips (RDU - Reconfigurable Dataflow Units) and provides a cloud platform for running LLMs with extremely fast inference speeds. Their SambaNova Cloud offers free-tier access to popular models like Llama and DeepSeek with industry-leading throughput.
Baseten is a model inference platform that lets developers deploy and scale ML models with high-performance GPU infrastructure. It supports custom model deployments with autoscaling, and hosts popular open-source models through its Truss serving framework.
Vast.ai is a decentralized GPU marketplace that connects GPU owners with AI developers, offering some of the lowest prices in the market through auction-based pricing. The platform provides access to a wide range of GPUs from consumer-grade to data center hardware for training, fine-tuning, and inference workloads.
Novita AI provides affordable API access to open-source AI models including LLMs, image generation, and video models. The platform offers competitive pricing on popular models like Llama, Mistral, and Stable Diffusion, with pay-per-use billing and no minimum commitments.
The default way of running on-device AI at scale — deploy and orchestrate AI models on edge devices.
The fastest multimodal inference OS — optimized infrastructure for running multimodal AI models at scale.